Most adult tissues have minimal capacity for regeneration following injury or disease. This lack of regenerative potential presents a major clinical challenge in treating a broad range of diseases, including stroke, myocardial infarction, bone defects, spinal cord injury, diabetes, and kidney failure. To address this clinical need, a major goal of regenerative medicine is to use stem cells to repair or replace damaged or missing tissue. One of the most promising cell types for stem cell-based regenerative applications is adipose-derived stromal cells (ASCs), as they are readily isolated in large numbers from minimally invasive lipoaspiration procedures and can differentiate into several different tissue types. Many investigators have demonstrated that ASCs can differentiate into several tissue types and have proposed using these cells for tissue regeneration;this field is still in its infancy. On of the major challenges that has not been solved is the heterogeneous nature of stem cells. While stem cell populations are known to be heterogeneous, the functional consequences of this heterogeneity have not been fully elucidated. The problem of undefined heterogeneity within stem cells must be overcome before they can be used effectively for therapeutic applications. The first step to understand this heterogeneity is to elucidate the gene expression profiles of these complex cells. To address this need, we have developed a novel high resolution, high-throughput method to analyze the concurrent expression of multiple genes across multiple individual cells. The central hypothesis of this proposal is that the transcriptional heterogeneity within human adipose derived stromal cells can be defined on the single cell level, which will allow selection of cell subgroups with the greatest potential for use in cell-based therapies.